Nineteenth-century medical ethics is often reconstructed through formal codes or retrospectively interpreted through concepts developed by twentieth-century bioethics. This study examines how duties, limits of professional authority, and responsibilities toward patients, colleagues, the public, and state institutions were articulated within the French-language Gazette–Société professional milieu in Constantinople between 1857 and 1876. We conducted a structured historical qualitative content analysis of digitized issues and annual volumes. Candidate texts were screened for sustained actor-level normative reasoning rather than contemporary ethical salience alone. Only E2 (substantial embedded normative reasoning) and E3 (explicit sustained ethical/deontological argument) records entered the analytical corpus. Included publication units were coded into nine primary themes and five source-origin categories, with serial/duplicate reconciliation, source-coverage auditing, and repeated boundary review. The analytical corpus contained 251 verified units: 118 E3 and 133 E2. Professional identity, deontology, and self-regulation was the largest primary category (109/251), followed by public-health governance and regulation (58/251). The remaining verified units were distributed across assistance and social obligation, medico-legal and expert responsibility, therapeutic responsibility, duties concerning the scientific record and publication, mental-health and institutional authority, patient/family decision-making, and professional secrecy. Because source coverage is uneven, the study does not interpret differences in the numbers recovered from the three descriptive intervals as temporal increases or decreases in ethical discussion. Within the Gazette–Société milieu, medical ethics appeared as an embedded normative practice rather than a discrete specialty. Across the available material, professional authority was articulated through historically specific languages of duty, dignity, conscience, morality, humanity, honour, and responsibility in professional, clinical, sanitary, forensic, humanitarian, and communicative settings. These findings characterize a particular institutional and linguistic professional arena and are not presented as representative of medical ethics throughout the Ottoman Empire. Not applicable.
AI chatbots are increasingly used as therapists for mental health problems. A potential benefit of this technology is that, unlike human practitioners, it is not affected by waiting times. However, its use also raises ethical challenges, and while ethical analyses are growing, perspectives from relevant stakeholders remain understudied. This qualitative study examines ethical questions surrounding the use of AI chatbots as therapists for people with mental health problems. We conducted online 90-minute focus groups with mental healthcare practitioners (psychiatrists, psychologists, psychotherapists, physicians, psychiatric nurses), ethicists, AI experts, and legal professionals in the Netherlands. A topic list based on a previously published scoping review guided the discussions, and a vignette served as a prompt for ethical reflection. The discussions were analysed using thematic content analysis. As the study progressed, methods were refined to enhance validity and reliability, for example, by adjusting the topic list, vignette or group composition. Transcripts were reviewed, corrected and coded in MAXQDA. Participants across all stakeholder groups expressed caution or reluctance toward using AI chatbots in mental healthcare due to unresolved ethical and legal concerns. Key worries included potential harm to users, uncertainty about responsibility for adverse outcomes, and risks including harmful output or AI hallucinations, excessive screen time, and limited effectiveness. While most participants preferred human-to-human contact, they acknowledged that some patients might prefer chatbots and emphasised the importance of informed and autonomous choice. Privacy and confidentiality concerns were raised, particularly by legal professionals rather than by other groups. We distinguished three types of ethical concerns about AI chatbots in mental healthcare: general AI issues, concerns specific to AI in mental health contexts, and concerns that also apply to human therapists. Distinguishing between these categories is useful because potential solutions may come from different domains. Participants weighed the second category—concerns specific to AI in mental health contexts—especially heavily. Yet, as people already turn to chatbots for mental health support, we suggest the question is not whether they should be used, but under what conditions and with what level of risk acceptance their use can be responsible and safe.
Sudden cardiac death (SCD) is a devastating event not only for determining the cause of death but also for the health of surviving relatives, as autopsy findings may reveal hereditary heart disorders that imply detailed cardiological evaluation, genetic counseling, and cascade screening of family members. Beyond their informative value, communication of autopsy findings raises ethical issues related to transparency, disclosure of hereditary risk, professional responsibility, and family-centered care. Despite advances in post-mortem diagnostics, communication remains inconsistent, and bereaved families frequently report unmet informational and emotional needs. To our knowledge, this is the first expert consensus-based, network-derived communication framework for the Balkan region the Balkan region, integrating ethical principles with forensic, genetic and cardiological perspectives to support structured, family-centered post-mortem care. The authors examined current evidence regarding the ethical and practical challenges of communicating autopsy findings following SCD. Afterwards, a structured, network-based development process was carried out within seven Departments of Forensic Medicine with the aim to improve the quality and consistency of communication with bereaved families in the Balkan region. Participants developed communication pathway following sudden cardiac death. The proposed pathway emphasizes early family engagement, continuous communication throughout the investigation, structured communication of autopsy findings, family counseling in cases of suspected heritable cardiac disease, including referral for cardiological evaluation and genetic counseling when appropriate, cascade screening of at-risk relatives, and long-term follow-up. The pathway is intended as a practical communication framework and as a good practice in forensic medicine for pathologists. Communication of autopsy findings is an important part of postmortem care following sudden cardiac death, not just the transmission of diagnostic information. Beyond the conversation, there is an ethical responsibility to bereaved families and next of kin. Although current evidence is limited, it consistently supports structured communication with the bereaved family, respects family autonomy, and facilitates appropriate assessment of relatives in cases where a hereditary disease is suspected. This proposed framework may improve communication skills in forensic practice, strengthen multidisciplinary collaboration, and provide a basis for future validation studies and the development of evidence-based guidelines.
To investigate how stakeholders in Shenzhen—including regulators, developers, clinicians, and ethics committee members—understand and respond to the ethical challenges with medical AI. A qualitative study was performed using a semi-structured interview format involving focus group interviews. Shenzhen, China. Stratified purposive and convenience sampling were used. A total of 45 participants were recruited, including representatives from government agencies (n = 5), industry (n = 13), research institutions (n = 13), and medical institutions (n = 14). The study group developed a semi-structured interview guide for focus group interviews by experienced interviewers. Participants were encouraged to share their opinions and discuss personal topics. Data underwent thematic analysis and were coded and extracted using NVivo 11 software. The Chinese government and local authorities are promoting the AI industry with ethical governance in their plans. Key stakeholders in Shenzhen have concerns about safety and reliability of AI in healthcare, regulatory clarity in practice, responsibility allocation, and multidisciplinary cooperation. More explicit ethical guidance, better regulatory coordination, stronger cross-sector collaboration, and more institutional support are needed for ethical governance of medical AI. All stakeholders should address ethical issues in medical AI development and use. Shenzhen’s leadership in China’s healthcare AI can guide policy and practices in the city and other fast-growing areas.
Ethics education aims to prepare healthcare students to recognise and respond to ethical challenges in clinical practice, yet the ability to recognise an ethical theory may not correspond directly to the principles students endorse or to their experiences in clinical settings. The aim of this study was to examine the relationship between self-reported Kant-informed ethical orientation, recognition of a basic duty-based description of Kantian ethics, and perceived pressure to act against one’s moral principles during clinical practice among nursing students, and to identify educational and demographic factors associated with students’ ethical orientation. A cross-sectional survey was conducted among 205 undergraduate and postgraduate nursing students in Slovenia. Ethical orientation was assessed using the newly developed Kantian Ethical Orientation Scale for Nursing Students (KEOS-NS). Recognition of a basic duty-based description of Kantian ethics and perceived moral pressure during clinical practice were assessed using single items. Associations with KEOS-NS scores were examined using non-parametric tests and multiple linear regression; the relationship between employment in nursing and perceived moral pressure was examined using a chi-square test. Only 75 students (36.6
